Statistical modeling of global geogenic arsenic contamination in groundwater.

Contamination of groundwaters with geogenic arsenic poses a major health risk to millions of people. Although the main geochemical mechanisms of arsenic mobilization are well understood, the worldwide scale of affected regions is still unknown. In this study we used a large database of measured arsenic concentration in groundwaters (around 20,000 data points) from around the world as well as digital maps of physical characteristics such as soil, geology, climate, and elevation to model probability maps of global arsenic contamination.

Analyzing bank filtration by deconvoluting time series of electric conductivity.

Knowing the travel-time distributions from infiltrating rivers to pumping wells is important in the management of alluvial aquifers. Commonly, travel-time distributions are determined by releasing a tracer pulse into the river and measuring the breakthrough curve in the wells. As an alternative, one may measure signals of a time-varying natural tracer in the river and in adjacent wells and infer the travel-time distributions by deconvolution.

Ground water pollution by roof runoff infiltration evidenced with multi-tracer experiments.

The infiltration of urban roof runoff into well permeable subsurface material may have adverse effects on the ground water quality and endanger drinking water resources. Precipitation water from three different roofs of an industrial complex was channelled to a pit and infiltrated into a perialpine glaciofluvial gravel-and-sand aquifer. A shaft was constructed at the bottom of the pit and equipped with an array of TDR probes, lysimeters and suction cups that allowed measuring and sampling soil water at different depths.